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A dynamic stochastic frontier approach with persistent and transient inefficiency and unobserved heterogeneity

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  • Jean Joseph Minviel
  • Timo Sipiläinen

Abstract

This article introduces a dynamic stochastic frontier analysis (SFA) framework with unobserved heterogeneity, persistent and transient inefficiency effects, based on recent advances in the SFA literature. The newly developed dynamic frontier model is applied on a sample of French crop‐livestock farms. The estimates provide useful insights for the estimation of the technical efficiency scores as well as for the analysis of the associations of contextual drivers, such as public subsidies and indebtedness, with technical efficiency.

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  • Jean Joseph Minviel & Timo Sipiläinen, 2021. "A dynamic stochastic frontier approach with persistent and transient inefficiency and unobserved heterogeneity," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 575-589, July.
    • Handle: RePEc:bla:agecon:v:52:y:2021:i:4:p:575-589
    DOI: 10.1111/agec.12636
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    5. Haokun Wang & Hong Chen & Tuyen Thi Tran & Shuai Qin, 2022. "An Analysis of the Spatiotemporal Characteristics and Diversity of Grain Production Resource Utilization Efficiency under the Constraint of Carbon Emissions: Evidence from Major Grain-Producing Areas ," IJERPH, MDPI, vol. 19(13), pages 1-25, June.
    6. Xiaochun Zhao & Huixin Xu & Qun Sun, 2022. "Research on China’s Carbon Emission Efficiency and Its Regional Differences," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    7. Guoting Yang & Jing Li & Zhen Liu & Yitao Zhang & Xiangbo Xu & Hong Zhang & Yan Xu, 2022. "Research Trends in Crop–Livestock Systems: A Bibliometric Review," IJERPH, MDPI, vol. 19(14), pages 1-14, July.
    8. Troncoso, Ricardo & Cabas, Juan & Guesmi, Bouali & Gil, José María, 2023. "A cross-country comparison of pig production systems performance: Evidence from EU countries," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 23(02), December.
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